Refined RIP-seq protocol for epitranscriptome analysis with low input materials

Yong Zeng1, Shiyan Wang1, Shanshan Gao2

  • 1Princess Margaret Cancer Centre/University Health Network, Toronto, Ontario, Canada.

Plos Biology
|September 14, 2018
PubMed

Insights

Researchers developed a low-input N6-Methyladenosine (m6A) RNA sequencing method for patient tumors. This technique profiles the m6A epitranscriptome from limited samples, revealing mRNA and protein level discrepancies.

Area of Science:

  • Molecular Biology
  • Epigenetics
  • Cancer Research

Background:

  • N6-Methyladenosine (m6A) is the most abundant internal mRNA modification in mammals.
  • m6A RNA immunoprecipitation followed by high-throughput sequencing (MeRIP-seq) maps m6A sites but requires substantial RNA input.
  • Current MeRIP-seq protocols are unsuitable for limited clinical samples like patient tumors.

Purpose of the Study:

  • To refine the m6A MeRIP-seq protocol for low-input RNA samples.
  • To enable m6A epitranscriptome profiling in patient tumors.
  • To investigate m6A dynamics correlating mRNA and protein levels in lung adenocarcinoma.

Main Methods:

  • Optimization of m6A MeRIP-seq parameters including RNA input, fragmentation, antibody selection, and washing/elution conditions.
  • Development of a post-amplification rRNA depletion strategy for low-input samples.
  • Bioinformatic analysis pipeline for m6A peak identification and integration with transcriptome and proteome data.

Main Results:

  • A refined m6A MeRIP-seq protocol successfully profiled the epitranscriptome from 500 ng of total RNA.
  • Approximately 12,000 high signal-to-noise m6A peaks were identified in lung adenocarcinoma patient tumors.
  • Integrative analysis revealed m6A-driven dynamics explaining mRNA-protein level discordance.

Conclusions:

  • The optimized low-input m6A MeRIP-seq method is effective for clinical sample analysis.
  • This technique facilitates the study of m6A epitranscriptome dynamics in patient tumors.
  • The findings provide a foundation for understanding m6A mechanisms in clinical settings.

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